Generic Reword Model of Partially Observed Markov decision processes (POMDP) for pattern detection

Research-based on deep reinforcement learning and stochastic modelization for bottleneck phenomenon optimization is the motivation for this development, by using big data technology and IoT-based sensors. In this paper we propose a generic representation of bottleneck phenomenon who narrows (limit) the possible actions in the observed field, such as the impact of the dangerous epidemics on human activity, economic, social and many other areas, which disturb the related schedule process, where the activity threshold must be included in an interval of actions in order to not enter a bottleneck phenomenon. On the other hand, a powerful reinforcement learning model, who handle tough situations that approach real-world complexity, in this level the data of the previous level well allow a better new action that may yield higher rewards in the next transitions, as well as the precise representation of the reward during the studied situation level, allows more wisdom for the future examination

Numerical analysis of a hybrid air photovoltaic panel (PV)

During the photovoltaic conversion of solar panels, a significant amount of heat is generated, which causes an increase in the temperature of photovoltaic cells and decreases their efficiency and reliability. This negative effect of heat is caused by a part of the solar radiation that is not absorbed by the solar panels, which leads to heat and weakens its performance. Many efforts have been made to reduce this heating effect on the performance of the PV system, such as combining PV and thermal systems to form a hybrid PVT complex that produces both electricity and heat. Gambit and Fluent 6.3.26 software were used for geometry construction and numerical simulations. This work aims to improve the electrical performance of PV cells by enhancing the heat recovered from PVT panels. For this purpose, we performed a numerical simulation of three configurations (3) of PVT panels integrated with TFMS. We analyzed and compared a single air PVT module (without fins), an air PVT module with two fins, and an air PVT module with four fins. The obtained results represent the variations of the contours and the temperature profiles as well as the flow velocity as a function of the flow rates, and the results show that the use of air and the integration of fins has a significant effect on the cooling of the PVT panel elements and thus allowing to improve its performance

Extraction of rules from a contingency table in the case of complex Big Data type systems

This article describes a modeling approach based on data from a contingency table. We develop a step-by-step procedure based on the definition of a knowledge extractor using entropic concepts. The limit extraction threshold is chosen according to a multi-criteria analysis. Rules in symbolic form endowed with a truth coefficient and an efficiency coefficient are then deduced and constitute the model of the syst